We were using the wrong “maximal” model! This is a quick notebook to check what we see when we use the right maximal model to determine how many factors to extract.
7-9yo US Children, 2 characters
Maximal structure, oblimin rotation
convergence not obtained in GPFoblq. 1000 iterations used. A loading greater than abs(1) was detected. Examine the loadings carefully.

Reduced structure, oblimin rotation

Alternative factor retention methods
Parallel analysis suggests that the number of factors = 3 and the number of components = 3

Very Simple Structure
Call: vss(x = x, n = n, rotate = rotate, diagonal = diagonal, fm = fm,
n.obs = n.obs, plot = plot, title = title, use = use, cor = cor)
VSS complexity 1 achieves a maximimum of 0.64 with 2 factors
VSS complexity 2 achieves a maximimum of 0.78 with 3 factors
The Velicer MAP achieves a minimum of 0.01 with 3 factors
BIC achieves a minimum of -2636.75 with 3 factors
Sample Size adjusted BIC achieves a minimum of -549.78 with 5 factors
Statistics by number of factors
vss1 vss2 map dof chisq prob sqresid fit RMSEA BIC SABIC complex
1 0.61 0.00 0.0207 740 1846 7.7e-96 48 0.61 0.091 -2093 251 1.0
2 0.64 0.77 0.0121 701 1171 3.8e-26 28 0.77 0.063 -2561 -340 1.3
3 0.57 0.78 0.0090 663 892 5.7e-09 22 0.82 0.048 -2637 -536 1.6
4 0.53 0.75 0.0096 626 803 1.9e-06 20 0.84 0.044 -2529 -545 1.9
5 0.52 0.73 0.0099 590 721 1.6e-04 18 0.85 0.041 -2419 -550 2.0
6 0.49 0.71 0.0107 555 652 2.7e-03 17 0.86 0.038 -2302 -544 2.1
7 0.50 0.71 0.0113 521 586 2.5e-02 16 0.87 0.034 -2187 -536 2.3
8 0.47 0.67 0.0121 488 527 1.1e-01 14 0.88 0.031 -2071 -525 2.4
eChisq SRMR eCRMS eBIC
1 4475 0.118 0.121 536
2 1568 0.070 0.074 -2164
3 819 0.051 0.055 -2710
4 690 0.046 0.052 -2642
5 566 0.042 0.048 -2575
6 482 0.039 0.046 -2472
7 402 0.035 0.043 -2371
8 337 0.032 0.041 -2261

Clustering within reduced factor space

7-9yo US Children, 9 characters
Maximal structure, oblimin rotation
convergence not obtained in GPFoblq. 1000 iterations used. A loading greater than abs(1) was detected. Examine the loadings carefully.

Reduced structure, oblimin rotation

Alternative factor retention methods
The estimated weights for the factor scores are probably incorrect. Try a different factor extraction method.
Parallel analysis suggests that the number of factors = 3 and the number of components = 3

Very Simple Structure
Call: vss(x = x, n = n, rotate = rotate, diagonal = diagonal, fm = fm,
n.obs = n.obs, plot = plot, title = title, use = use, cor = cor)
VSS complexity 1 achieves a maximimum of 0.82 with 1 factors
VSS complexity 2 achieves a maximimum of 0.9 with 2 factors
The Velicer MAP achieves a minimum of 0.02 with 3 factors
BIC achieves a minimum of -447.53 with 3 factors
Sample Size adjusted BIC achieves a minimum of -41.12 with 7 factors
Statistics by number of factors
vss1 vss2 map dof chisq prob sqresid fit RMSEA BIC SABIC complex
1 0.82 0.00 0.041 170 542 1.8e-40 14.1 0.82 0.141 -276 262 1.0
2 0.77 0.90 0.032 151 374 6.8e-21 8.1 0.90 0.117 -353 125 1.2
3 0.56 0.88 0.022 133 192 5.7e-04 5.2 0.93 0.068 -448 -27 1.5
4 0.57 0.88 0.027 116 156 7.9e-03 4.7 0.94 0.062 -402 -35 1.6
5 0.56 0.87 0.032 100 125 4.5e-02 4.0 0.95 0.055 -356 -40 1.7
6 0.49 0.76 0.036 85 102 1.0e-01 3.5 0.96 0.052 -307 -38 2.0
7 0.49 0.74 0.042 71 76 3.2e-01 3.0 0.96 0.039 -266 -41 2.1
8 0.48 0.77 0.048 58 55 5.8e-01 2.5 0.97 0.023 -224 -40 2.1
eChisq SRMR eCRMS eBIC
1 690 0.121 0.128 -128
2 279 0.077 0.087 -448
3 82 0.042 0.050 -558
4 65 0.037 0.048 -494
5 46 0.031 0.043 -435
6 32 0.026 0.039 -377
7 21 0.021 0.035 -321
8 12 0.016 0.029 -267

Clustering within reduced factor space

4-6yo US Children
Maximal structure, oblimin rotation
A loading greater than abs(1) was detected. Examine the loadings carefully.

Reduced structure, oblimin rotation

Alternative factor retention methods
The estimated weights for the factor scores are probably incorrect. Try a different factor extraction method.
Parallel analysis suggests that the number of factors = 2 and the number of components = 1

An ultra-Heywood case was detected. Examine the results carefully
Very Simple Structure
Call: vss(x = x, n = n, rotate = rotate, diagonal = diagonal, fm = fm,
n.obs = n.obs, plot = plot, title = title, use = use, cor = cor)
VSS complexity 1 achieves a maximimum of 0.84 with 1 factors
VSS complexity 2 achieves a maximimum of 0.87 with 2 factors
The Velicer MAP achieves a minimum of 0.02 with 1 factors
BIC achieves a minimum of -521.5 with 1 factors
Sample Size adjusted BIC achieves a minimum of -46.41 with 4 factors
Statistics by number of factors
vss1 vss2 map dof chisq prob sqresid fit RMSEA BIC SABIC complex
1 0.84 0.00 0.018 170 298 4.7e-09 11.0 0.84 0.084 -521 16.0 1.0
2 0.62 0.87 0.019 151 242 3.5e-06 8.9 0.87 0.077 -486 -8.1 1.4
3 0.43 0.78 0.022 133 192 5.9e-04 7.8 0.88 0.068 -449 -28.2 1.9
4 0.34 0.67 0.023 116 146 3.1e-02 6.6 0.90 0.055 -413 -46.4 2.2
5 0.33 0.61 0.028 100 128 3.1e-02 5.9 0.91 0.057 -354 -37.8 2.4
6 0.32 0.60 0.033 85 104 8.1e-02 5.2 0.92 0.053 -306 -37.1 2.5
7 0.28 0.53 0.039 71 78 2.7e-01 4.5 0.93 0.042 -264 -39.8 2.6
8 0.31 0.55 0.046 58 57 5.3e-01 4.0 0.94 0.027 -223 -39.6 2.5
eChisq SRMR eCRMS eBIC
1 276 0.076 0.081 -544
2 180 0.062 0.069 -547
3 132 0.053 0.063 -509
4 87 0.043 0.055 -472
5 70 0.039 0.053 -412
6 53 0.033 0.050 -357
7 34 0.027 0.044 -308
8 23 0.022 0.040 -256

Clustering within reduced factor space

---
title: "Quick dimkid check"
output: html_notebook
---

We were using the wrong "maximal" model! This is a quick notebook to check what we see when we use the right maximal model to determine how many factors to extract.

```{r global_options, include = F}
knitr::opts_chunk$set(echo=F, warning=F, cache=F, message=F)
```

```{r libraries, include = F}
library(tidyverse)
library(lubridate)
library(psych)
library(rms)
library(dendextend)
```

```{r functions, include = F}
# make function to clean up kid data from US
clean_kid_us_fun <- function(df, n_trials, age_lower, age_upper) {
  
  if(!("age" %in% names(df))) {
    df <- df %>%
      mutate(age = NA)
  }
  
  df_clean <- df %>%
    mutate(dob = parse_datetime(dateOfBirth, "%m/%d/%y"),
           dot = parse_datetime(gsub("2017", "17", dateOfTest), "%m/%d/%y"),
           age = ifelse(is.na(age),
                        interval(start = dob, end = dot) /
                          duration(num = 1, units = "years"),
                        age)) %>%
    filter(trialNum <= n_trials) %>%
    filter((age >= age_lower & age < age_upper + 1) | # outside of age range
             is.na(age), # missing age
           (rt >= 250 | is.na(rt)), # fast RTs
           response %in% c("no", "kinda", "yes"), # skipped trials
           !is.na(subid), !is.na(capacity)) %>%
    mutate(responseNum = recode(response,
                                "no" = 0,
                                "kinda" = 0.5,
                                "yes" = 1),
           responseNum = as.numeric(responseNum)) %>%
    distinct(subid, capacity, responseNum) %>%
    mutate(capacity = recode(capacity,
                             "conscious" = "awareness",
                             "embarrassed" = "embarrassment",
                             "guilt" = "guilt",
                             "happy" = "happiness",
                             "love" = "love",
                             "pain" = "pain",
                             "pride" = "pride",
                             "depressed" = "sadness",
                             "fear" = "fear",
                             "nauseated" = "nausea",
                             "tired" = "fatigue",
                             "reasoning" = "figuring_out",
                             "angry" = "anger",
                             "hungry" = "hunger",
                             "disrespected" = "hurt_feelings",
                             "choices" = "choice",
                             "remembering" = "memory",
                             "temperature" = "temperature",
                             "depth" = "depth",
                             "odors" = "smell")) %>%
    spread(capacity, responseNum) %>%
    remove_rownames() %>%
    column_to_rownames("subid")
  
  return(df_clean)
  
}

# make function to determine max n_factors, given n_obs variables
max_fact_fun <- function(p) {
  
  s_moments <- function(p) {p*(p+1)/2}
  param_est <- function(p, k) {p*k + p - (k*(k-1)/2)}
  check_ok <- function(p, k) {
    a <- (p-k)^2
    b <- p+k
    return(ifelse(a>b, TRUE, FALSE))
  }
  
  df_check <- data.frame()
  for(i in 1:p){
    df_check[i,"check"] <- check_ok(p,i)
  }
  
  max <- df_check %>% filter(check) %>% nrow()
  return(max)
  
}

# make function to implement factor retention criteria
reten_fact_fun <- function(df, rot) {
  
  max_efa <- fa(df, nfactors = max_fact_fun(ncol(df)), rotate = "none")
  max_vacc <- max_efa$Vaccounted %>%
    data.frame() %>%
    rownames_to_column("stat") %>%
    gather(factor, value, -stat) %>%
    spread(stat, value) %>%
    filter(`SS loadings` > 1, `Proportion Explained` > 0.05)
  n_reten1 <- nrow(max_vacc)
  
  reten_efa <- fa(df, nfactors = n_reten1, rotate = rot)
  reten_loadings <- reten_efa$loadings[] %>%
    data.frame() %>%
    rownames_to_column("mc") %>%
    gather(factor, loading, -mc) %>%
    group_by(mc) %>%
    top_n(1, abs(loading)) %>%
    ungroup()
  n_reten2 <- reten_loadings %>%
    count(factor) %>%
    nrow()
    
  return(n_reten2)

}

# make function to plot heatmap of factor loadings
heatmap_fun <- function(df, n_factors, rot){
  
  efa <- fa(df, nfactors = n_factors, rotate = rot)
  loadings <- efa$loadings[] %>%
    fa.sort() %>%
    data.frame() %>%
    rownames_to_column("mc") %>%
    rownames_to_column("order") %>%
    mutate(order = as.numeric(order)) %>%
    gather(factor, loading, -c(mc, order))
  
  plot <- ggplot(loadings,
                 aes(x = factor, y = reorder(mc, desc(order)), fill = loading, 
                     label = format(round(loading, 2), nsmall = 2))) +
    geom_tile(color = "black") +
    geom_text(size = 3) +
    scale_x_discrete(position = "top") +
    scale_fill_distiller(limits = c(-1.02, 1.02), palette = "RdYlBu",
                         guide = guide_colorbar(barheight = 15)) +
    theme_minimal()
  
  return(plot)
  
}
```

```{r data, include = F, warning = FALSE}
# US 7-9yo, 2 characters
d_us79_2char <- read.csv("/Users/kweisman/Documents/Research (Stanford)/Projects/Dimkid/dimkid/data/children/run-01_2017-07-24_anonymized.csv") %>% clean_kid_us_fun(n_trials = 40, age_lower = 7, age_upper = 9)

# US 7-9yo, 9 characters
d_us79_9char <- read.csv("/Users/kweisman/Documents/Research (Stanford)/Projects/Dimkid/dimkid/data/children/run-02_2017-08-08_anonymized.csv") %>% clean_kid_us_fun(n_trials = 20, age_lower = 7, age_upper = 9)

# US 4-6yo, 9 characters
d_us46_9char <- read.csv("/Users/kweisman/Documents/Research (Stanford)/Projects/Dimkid/dimkid/data/children/run-03_2017-08-21_anonymized.csv") %>% clean_kid_us_fun(n_trials = 20, age_lower = 4, age_upper = 6)
```

# 7-9yo US Children, 2 characters

## Maximal structure, oblimin rotation

```{r, fig.width = 7, fig.asp = 0.5}
heatmap_fun(d_us79_2char, max_fact_fun(ncol(d_us79_2char)), "oblimin") +
  labs(title = "Factor loadings, maximal solution: 7-9yo US Children",
       subtitle = "2 characters, 40 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```

## Reduced structure, oblimin rotation

```{r, fig.width = 3, fig.asp = 1.5}
heatmap_fun(d_us79_2char, reten_fact_fun(d_us79_2char, "oblimin"), "oblimin") +
  labs(title = "Factor loadings, after retention: 7-9yo US Children",
       subtitle = "2 characters, 40 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```

## Alternative factor retention methods

```{r}
fa.parallel(d_us79_2char)
```

```{r}
VSS(d_us79_2char)
```

```{r, fig.width = 3, fig.asp = 1, include = F}
heatmap_fun(d_us79_2char, 5, "oblimin") +
  labs(title = "Factor loadings, BIC retention: 7-9yo US Children",
       subtitle = "2 characters, 40 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```

## Clustering within reduced factor space

```{r, fig.width = 4, fig.asp = 0.67}
# par(mar = c(1, 1, 1, 6))
clust <- fa(d_us79_2char, 
            reten_fact_fun(d_us79_2char, "oblimin"), "oblimin")$loadings[] %>%
  data.frame() %>%
  dist() %>%
  hclust()

clust %>%
  as.dendrogram() %>%
  set("labels_col", value = c("#a6cee3", "#1f78b4", "#b2df8a", "#33a02c",
                              "#fb9a99", "#e31a1c", "#fdbf6f", "#ff7f00", 
                              "#cab2d6", "#6a3d9a", "#ffff99", "#b15928"), 
      k = 6) %>%
  set("branches_lwd", 0.5) %>%
  # set("leaves_pch", 16) %>%
  # plot(horiz = T)
  as.ggdend() %>%
  ggplot(horiz = F) +
  geom_hline(yintercept = 2, lty = 2, color = "black") +
  coord_cartesian(ylim = c(-0.7, max(clust$height))) +
  labs(title = "Hierarchical clustering within reduced factor space: 7-9yo US Children",
       subtitle = "2 characters, 40 capacities, oblimin rotation")

rm(clust)
```


# 7-9yo US Children, 9 characters

## Maximal structure, oblimin rotation

```{r, fig.width = 4, fig.asp = 0.67}
heatmap_fun(d_us79_9char, max_fact_fun(ncol(d_us79_9char)), "oblimin") +
  labs(title = "Factor loadings, maximal solution: 7-9yo US Children",
       subtitle = "9 characters, 20 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```

## Reduced structure, oblimin rotation

```{r, fig.width = 3, fig.asp = 1}
heatmap_fun(d_us79_9char, reten_fact_fun(d_us79_9char, "oblimin"), "oblimin") +
  labs(title = "Factor loadings, after retention: 7-9yo US Children",
       subtitle = "9 characters, 20 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```


## Alternative factor retention methods

```{r}
fa.parallel(d_us79_9char)
```

```{r}
VSS(d_us79_9char)
```


## Clustering within reduced factor space

```{r, fig.width = 4, fig.asp = 0.67}
# par(mar = c(1, 1, 1, 6))
clust <- fa(d_us79_9char, 
            reten_fact_fun(d_us79_9char, "oblimin"), "oblimin")$loadings[] %>%
  data.frame() %>%
  dist() %>%
  hclust()

clust %>%
  as.dendrogram() %>%
  set("labels_col", value = c("#a6cee3", "#1f78b4", "#b2df8a", "#33a02c",
                              "#fb9a99", "#e31a1c", "#fdbf6f", "#ff7f00", 
                              "#cab2d6", "#6a3d9a", "#ffff99", "#b15928"), 
      k = 4) %>%
  set("branches_lwd", 0.5) %>%
  # set("leaves_pch", 16) %>%
  # plot(horiz = T)
  as.ggdend() %>%
  ggplot(horiz = F) +
  geom_hline(yintercept = 2, lty = 2, color = "black") +
  coord_cartesian(ylim = c(-0.7, max(clust$height))) +
  labs(title = "Hierarchical clustering within reduced factor space: 7-9yo US Children",
       subtitle = "9 characters, 20 capacities, oblimin rotation")

rm(clust)
```

# 4-6yo US Children

## Maximal structure, oblimin rotation

```{r, fig.width = 4, fig.asp = 0.67}
heatmap_fun(d_us46_9char, max_fact_fun(ncol(d_us46_9char)), "oblimin") +
  labs(title = "Factor loadings, maximal solution: 4-6yo US Children",
       subtitle = "9 characters, 20 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```

## Reduced structure, oblimin rotation

```{r, fig.width = 3, fig.asp = 1}
heatmap_fun(d_us46_9char, reten_fact_fun(d_us46_9char, "oblimin"), "oblimin") +
  labs(title = "Factor loadings, after retention: 4-6yo US Children",
       subtitle = "9 characters, 20 capacities, oblimin rotation",
       x = "", y = "", fill = "")
```


## Alternative factor retention methods

```{r}
fa.parallel(d_us46_9char)
```

```{r}
VSS(d_us46_9char)
```

## Clustering within reduced factor space

```{r, fig.width = 4, fig.asp = 0.67}
# par(mar = c(1, 1, 1, 6))
clust <- fa(d_us46_9char, 
            reten_fact_fun(d_us46_9char, "oblimin"), "oblimin")$loadings[] %>%
  data.frame() %>%
  dist() %>%
  hclust()

clust %>%
  as.dendrogram() %>%
  set("labels_col", 
      # value = colorRampPalette(solarized_pal()(8))(20),
      value = c("#a6cee3", "#1f78b4", "#b2df8a", "#33a02c",
                "#fb9a99", "#e31a1c", "#fdbf6f", "#ff7f00",
                "#cab2d6", "#6a3d9a", "#ffff99", "#b15928"),
      k = 6) %>%
  set("branches_lwd", 0.5) %>%
  # set("leaves_pch", 16) %>%
  # plot(horiz = T)
  as.ggdend() %>%
  ggplot(horiz = F) +
  geom_hline(yintercept = 2, lty = 2, color = "black") +
  coord_cartesian(ylim = c(-0.7, max(clust$height))) +
  labs(title = "Hierarchical clustering within reduced factor space: 4-6yo US Children",
       subtitle = "9 characters, 20 capacities, oblimin rotation")

rm(clust)
```

